Waystream initiates research project in machine learning, AI

waystremThe Swedish technology company Waystream has initiated a research project on machine learning and artificial intelligence (AI) in relation to operation of broadband and city networks

The aim of the project is to evaluate various methods for machine learning and artificial intelligence to be used in the operation of fibre-based broadband networks in order to improve availability and reliability for end-users.

The research project has been initiated by Waystream and consists of participants from several organisations.

Johan Sandell, chief technology officer at Waystream, said, “Artificial intelligence and machine learning create new opportunities for analysing large amounts of data to find deviations from what is normal. Applying this to the type of information provided by Waystream’s switches through telemetry allows us to find errors that affect network traffic much faster than before.

“For a city network operator, it means that you can get alarms about anomalies in the network that you would not otherwise have detected before it already affects large end-user groups. So the goal is to investigate new tools for network operators to use to locate and even predict errors and take action that reduces the impact on end-users.”

At the end of 2019, Waystream introduced telemetry technology in their products. By using telemetry, operators can collect, at every minute, thousands of operational parameters from each switch.

These parameters give details on the performance of the network. There can be hundreds, even thousands of switches within a large network. Thus, active service assurance and monitoring provide a unique insight into how the network actually operates.

“It’s a huge amount of data available for analysis. More than what a human alone can keep track of. At the same time, each parameter conveys important information. Therefore, machine learning, where the systems learn what is normal at any given time each day, can be a powerful tool. When any of these thousands of parameters deviate from the normal, you can do an automated analysis and alert the operating staff if necessary. That is the goal,’ explained Sandell.

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